A new paradigm: focusing on Work to be Done

Much of what we read about with artificial intelligence, deep learning and robots can present a fear that our jobs are simply going, vanishing fairly soon. Technology, machines and information solutions will take over in this new world of accelerating technology with the concern of “so then, what do we do?

Well, I believe we have a real chance to, at last, celebrate. Yes celebrate, we can finally be liberated! Ever since the industrial revolution, we have been caught up in the productivity and efficiency trap, in the monotony of repeating work.

Today we are on the cusp of changing that.  Can you imagine all those boring, repetitive jobs we are faced with today can be simply handed over to machine intelligence, just happy to do the task at hand? Surely, if we manage this correctly it can release us up, it can enable our ingenuity to thrive. Continue reading


A New Integrated Innovation Engagement System

I have written extensively, certainly over the past eighteen months, about our need to take innovation into a new era, designed for today and tomorrow’s “fit for purpose”. Below you will see my view of how I see this sketched out, as my suggested concept outline. Does it make sense?

We have this compelling need to have a new cycle of innovation design. A more integrated solution that takes our understanding of innovation and how to manage it, into the realms of ecosystems and platforms in its design and thinking.

I wrote a piece “Jumping to a fresh cycle of innovation design” that stated much of what I saw as any design intent.

” We need to increasingly rely on problem-solving techniques that we generate through greater automated discovery and inquiry, those that emerge from analysis and data mining. So, we seek out greater applied science knowledge we will use it to support and develop practical applications based on technology and innovation. Utilitarian in its principles, seeking real-world use and implementation through a more creative, collaborative environment, leading to more discoveries that distinctly ‘blend’ the lab application with the customer discovery of unmet need. Through a blend of pattern recognition, predictive analytics and exploring cognitive computing we can change much with innovation”

“We have been steadily learning to adapt what we knew inside an organization with what we should increasingly listen to outside it. There has been an increasing emphasis on linking concepts in new and novel products and services, increasingly closer to these customer needs and desires.

We need to consider how big data and analytics, technology and a far more creative thinking needs to be applied collectively but in greater constellations of partners. We need to get far more comfortable with working in ecosystems, managed in platform designs to work more collaboratively. Continue reading